Agent-Centric Visual Reinforcement Learning under Dynamic Perturbations
arXiv:2604.24661v1 Announce Type: new
Abstract: Visual reinforcement learning aims to empower an agent to learn policies from visual observations, yet it remains vulnerable to dynamic visual perturbations, such as unpredictable shifts in corruption ty…